diff --git a/Eigen/src/SVD/JacobiSVD.h b/Eigen/src/SVD/JacobiSVD.h index 89ace381e..7a5821d4f 100644 --- a/Eigen/src/SVD/JacobiSVD.h +++ b/Eigen/src/SVD/JacobiSVD.h @@ -359,29 +359,42 @@ struct svd_precondition_2x2_block_to_be_real SVD; typedef typename SVD::Index Index; - static void run(typename SVD::WorkMatrixType&, SVD&, Index, Index) {} + typedef typename MatrixType::RealScalar RealScalar; + static bool run(typename SVD::WorkMatrixType&, SVD&, Index, Index, RealScalar&) { return true; } }; template struct svd_precondition_2x2_block_to_be_real { typedef JacobiSVD SVD; + typedef typename SVD::Index Index; typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::RealScalar RealScalar; - typedef typename SVD::Index Index; - static void run(typename SVD::WorkMatrixType& work_matrix, SVD& svd, Index p, Index q) + static bool run(typename SVD::WorkMatrixType& work_matrix, SVD& svd, Index p, Index q, RealScalar& maxDiagEntry) { using std::sqrt; + using std::abs; + using std::max; Scalar z; JacobiRotation rot; RealScalar n = sqrt(numext::abs2(work_matrix.coeff(p,p)) + numext::abs2(work_matrix.coeff(q,p))); - + + const RealScalar considerAsZero = (std::numeric_limits::min)(); + const RealScalar precision = NumTraits::epsilon(); + if(n==0) { - z = abs(work_matrix.coeff(p,q)) / work_matrix.coeff(p,q); - work_matrix.row(p) *= z; - if(svd.computeU()) svd.m_matrixU.col(p) *= conj(z); - if(work_matrix.coeff(q,q)!=Scalar(0)) + // make sure first column is zero + work_matrix.coeffRef(p,p) = work_matrix.coeffRef(q,p) = Scalar(0); + + if(abs(numext::imag(work_matrix.coeff(p,q)))>considerAsZero) + { + // work_matrix.coeff(p,q) can be zero if work_matrix.coeff(q,p) is not zero but small enough to underflow when computing n + z = abs(work_matrix.coeff(p,q)) / work_matrix.coeff(p,q); + work_matrix.row(p) *= z; + if(svd.computeU()) svd.m_matrixU.col(p) *= conj(z); + } + if(abs(numext::imag(work_matrix.coeff(q,q)))>considerAsZero) { z = abs(work_matrix.coeff(q,q)) / work_matrix.coeff(q,q); work_matrix.row(q) *= z; @@ -395,19 +408,25 @@ struct svd_precondition_2x2_block_to_be_real rot.s() = work_matrix.coeff(q,p) / n; work_matrix.applyOnTheLeft(p,q,rot); if(svd.computeU()) svd.m_matrixU.applyOnTheRight(p,q,rot.adjoint()); - if(work_matrix.coeff(p,q) != Scalar(0)) + if(abs(numext::imag(work_matrix.coeff(p,q)))>considerAsZero) { - Scalar z = abs(work_matrix.coeff(p,q)) / work_matrix.coeff(p,q); + z = abs(work_matrix.coeff(p,q)) / work_matrix.coeff(p,q); work_matrix.col(q) *= z; if(svd.computeV()) svd.m_matrixV.col(q) *= z; } - if(work_matrix.coeff(q,q) != Scalar(0)) + if(abs(numext::imag(work_matrix.coeff(q,q)))>considerAsZero) { z = abs(work_matrix.coeff(q,q)) / work_matrix.coeff(q,q); work_matrix.row(q) *= z; if(svd.computeU()) svd.m_matrixU.col(q) *= conj(z); } } + + // update largest diagonal entry + maxDiagEntry = max EIGEN_EMPTY (maxDiagEntry,max EIGEN_EMPTY (abs(work_matrix.coeff(p,p)), abs(work_matrix.coeff(q,q)))); + // and check whether the 2x2 block is already diagonal + RealScalar threshold = max EIGEN_EMPTY (considerAsZero, precision * maxDiagEntry); + return abs(work_matrix.coeff(p,q))>threshold || abs(work_matrix.coeff(q,p)) > threshold; } }; @@ -424,22 +443,23 @@ void real_2x2_jacobi_svd(const MatrixType& matrix, Index p, Index q, JacobiRotation rot1; RealScalar t = m.coeff(0,0) + m.coeff(1,1); RealScalar d = m.coeff(1,0) - m.coeff(0,1); - if(t == RealScalar(0)) + if(d == RealScalar(0)) { - rot1.c() = RealScalar(0); - rot1.s() = d > RealScalar(0) ? RealScalar(1) : RealScalar(-1); + rot1.s() = RealScalar(0); + rot1.c() = RealScalar(1); } else { - RealScalar t2d2 = numext::hypot(t,d); - rot1.c() = abs(t)/t2d2; - rot1.s() = d/t2d2; - if(tmakeJacobi(m,0,1); - *j_left = rot1 * j_right->transpose(); + *j_left = rot1 * j_right->transpose(); } } // end namespace internal @@ -826,6 +846,7 @@ JacobiSVD::compute(const MatrixType& matrix, unsig check_template_parameters(); using std::abs; + using std::max; allocate(matrix.rows(), matrix.cols(), computationOptions); // currently we stop when we reach precision 2*epsilon as the last bit of precision can require an unreasonable number of iterations, @@ -857,6 +878,7 @@ JacobiSVD::compute(const MatrixType& matrix, unsig } /*** step 2. The main Jacobi SVD iteration. ***/ + RealScalar maxDiagEntry = m_workMatrix.cwiseAbs().diagonal().maxCoeff(); bool finished = false; while(!finished) @@ -872,25 +894,27 @@ JacobiSVD::compute(const MatrixType& matrix, unsig // if this 2x2 sub-matrix is not diagonal already... // notice that this comparison will evaluate to false if any NaN is involved, ensuring that NaN's don't // keep us iterating forever. Similarly, small denormal numbers are considered zero. - using std::max; - RealScalar threshold = (max)(considerAsZero, precision * (max)(abs(m_workMatrix.coeff(p,p)), - abs(m_workMatrix.coeff(q,q)))); - // We compare both values to threshold instead of calling max to be robust to NaN (See bug 791) + RealScalar threshold = max EIGEN_EMPTY (considerAsZero, precision * maxDiagEntry); if(abs(m_workMatrix.coeff(p,q))>threshold || abs(m_workMatrix.coeff(q,p)) > threshold) { finished = false; - // perform SVD decomposition of 2x2 sub-matrix corresponding to indices p,q to make it diagonal - internal::svd_precondition_2x2_block_to_be_real::run(m_workMatrix, *this, p, q); - JacobiRotation j_left, j_right; - internal::real_2x2_jacobi_svd(m_workMatrix, p, q, &j_left, &j_right); + // the complex to real operation returns true is the updated 2x2 block is not already diagonal + if(internal::svd_precondition_2x2_block_to_be_real::run(m_workMatrix, *this, p, q, maxDiagEntry)) + { + JacobiRotation j_left, j_right; + internal::real_2x2_jacobi_svd(m_workMatrix, p, q, &j_left, &j_right); - // accumulate resulting Jacobi rotations - m_workMatrix.applyOnTheLeft(p,q,j_left); - if(computeU()) m_matrixU.applyOnTheRight(p,q,j_left.transpose()); + // accumulate resulting Jacobi rotations + m_workMatrix.applyOnTheLeft(p,q,j_left); + if(computeU()) m_matrixU.applyOnTheRight(p,q,j_left.transpose()); - m_workMatrix.applyOnTheRight(p,q,j_right); - if(computeV()) m_matrixV.applyOnTheRight(p,q,j_right); + m_workMatrix.applyOnTheRight(p,q,j_right); + if(computeV()) m_matrixV.applyOnTheRight(p,q,j_right); + + // keep track of the largest diagonal coefficient + maxDiagEntry = max EIGEN_EMPTY (maxDiagEntry,max EIGEN_EMPTY (abs(m_workMatrix.coeff(p,p)), abs(m_workMatrix.coeff(q,q)))); + } } } }